How to Keep AI Agents Running in Production for Under $6 a Month

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AI agents commonly fail in production due to stateful session timeouts, bloated dependencies, and escalating costs, according to a technical guide published on DEV Community. The guide recommends storing agent state externally using Redis or SQLite so it persists across restarts and supports horizontal scaling. Developers are advised to strip non-critical packages and use local LLMs such as llama-cpp-python instead of external APIs to reduce inference costs. A free-tier cron job or GitHub Actions workflow can ping the agent every five minutes and trigger an automatic restart if it goes down. Using platforms like Fly.io or Railway for hosting, the total infrastructure cost can be kept as low as $5.70 per month.

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